/Hyperspectral-Imaging

Hyperspectral Imaging


（From A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation）

I am currently working on tensor model-guided data-driven approaches in hyperspectral remote sensing.

Last Update: 2024/2/5

Surveys

  • [2024] Beyond Supervised Learning in RemoteSensing: A Systematic Review of Deep Learning Approaches, IEEE JSTARS [Paper]
  • [2023] From Single- to Multi-Modal Remote Sensing Imagery Interpretation: A Survey and Taxonomy, Science China Information Sciences [Paper]
  • [2023] Remote Sensing Object Detection Meets Deep Learning: A Meta-Review of Challenges and Advances, arXiv [Paper]
  • [2023] Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review, IEEE GRSM [Paper]
  • [2023] A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation, Science China Information Sciences [Paper]
  • [2023] Multispectral and Hyperspectral Image Fusion In Remote Sensing: A Survey, Information Fusion [Paper]
  • [2023] Hyperspectral Image Denoising: From Model-Driven, Data-Driven, to Model-Data-Driven, IEEE TNNLS [Paper]
  • [2023] Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review, International Journal of Applied Earth Observation and Geoinformation [Paper]
  • [2023] Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing: A Summary of Current Methods, IEEE SPM [Paper]
  • [2023] Tensor Computation for Data Analysis, Springer [Book]
  • [2022] Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects, IEEE JSTARS [Paper]
  • [2022] Low-Rank and Sparse Representation for Hyperspectral Image Processing: A Review, IEEE GRSM [Paper]
  • [2022] Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review, IEEE JSTARS [Paper]
  • [2022] Machine Learning in Pansharpening: A Benchmark, from Shallow to Deep Networks, IEEE GRSM [Paper] [Python]
  • [2022] Hyperspectral Anomaly Detection Based on Machine Learning: An Overview, IEEE JSTARS [Paper]
  • [2022] Hyperspectral Anomaly Detection: A Survey, IEEE GRSM [Paper]
  • [2022] Hyperspectral Anomaly Detection Using Deep Learning: A Review, Remote Sensing [Paper]
  • [2022] Domain Adaptation in Remote Sensing Image Classification: A Surveys, IEEE JSTARS [Paper]
  • [2022] Multi-View Learning for Hyperspectral Image Classification: An Overview, Neurocomputing [Paper]
  • [2021] Recent Advances and New Guidelines on Hyperspectral and Multispectral Image Fusion, Information Fusion [Paper]
  • [2021] Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects, IEEE JSTARS [Paper] [Python]
  • [2021] Multimodal Hyperspectral Remote Sensing: An Overview and Perspective, Science China Information Sciences [Paper]
  • [2021] Interpretable Hyperspectral Artificial Intelligence: When Non-Convex Modeling meets Hyperspectral Remote Sensing, IEEE GRSM [Paper]
  • [2021] A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samples, Neurocomputing [paper] [Python]
  • [2021] Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects, IEEE JSTARS [Paper] [Python]
  • [2020] Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep: Overview and Toolbox, IEEE GRSM [Paper] [Matlab]
  • [2020] Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture, Remote Sensing [Paper]

Classification

  • [2024] Feedback Band Group and Variation Low-Rank Sparse Model for Hyperspectral Image Anomaly Detection, IEEE TGRS [Paper]
  • [2024] GraphGST: Graph Generative Structure-Aware Transformer for Hyperspectral Image Classification, IEEE TGRS [Paper] [Python]
  • [2023] Universal Domain Adaptation for Remote Sensing Image Scene Classification, IEEE TGRS [Paper] [Python]
  • [2023] UCSL: Toward Unsupervised Common Subspace Learning for Cross-Modal Image Classification, IEEE TGRS [Paper] [Matlab]
  • [2023] Multilevel Spatial Feature-Based Manifold Metric Learning for Domain Adaptation in Remote Sensing Image Classification, IEEE TGRS [Paper]
  • [2022] Weighted Correlation Embedding Learning for Domain Adaptation, IEEE TIP [Paper] [Matlab]
  • [2022] Unsupervised Domain-Adaptation-Based Tensor Feature Learning With Structure Preservation, IEEE TAI [Paper] [Matlab]
  • [2020] Domain Adaptation Based on Correlation Subspace Dynamic Distribution Alignment for Remote Sensing Image Scene Classification, IEEE TGRS [Paper]
  • [2019] CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences, IEEE TGRS [Paper] [Matlab]
  • [2019] Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation, IEEE TNNLS [Paper] [Matlab]
  • [2019] LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation, IEEE TIP [Paper]
  • [2017] Structure Preserving Transfer Learning for Unsupervised Hyperspectral Image Classification, IEEE GRSL [Paper]
  • [2017] Domain Adaptation Using Representation Learning for the Classification of Remote Sensing Images, IEEE JSTARS [Paper]
  • [2016] Domain Adaptation for the Classification of Remote Sensing Data: An Overview of Recent Advances, IEEE GRSM [Paper]
  • [2015] Semisupervised Transfer Component Analysis for Domain Adaptation in Remote Sensing Image Classification, IEEE TGRS Paper]

Clustering

  • [2024] Spatial and Cluster Structural Prior-Guided Subspace Clustering for Hyperspectral Image, IEEE TGRS [Paper]
  • [2023] Diffusion Subspace Clustering for Hyperspectral Images, IEEE JSTARS [Paper]
  • [2022] Sparsity Regularized Deep Subspace Clustering for Multicriterion-Based Hyperspectral Band Selection, IEEE TGRS [Paper]
  • [2022] Heterogeneous Regularization-Based Tensor Subspace Clustering for Hyperspectral Band Selection, IEEE TNNLS [Paper]
  • [2022] Deep Low-Rank Graph Convolutional Subspace Clustering for Hyperspectral Image, IEEE TGRS [Paper]
  • [2022] Tensorial Multiview Subspace Clustering for Polarimetric Hyperspectral Images, IEEE TGRS [Paper]
  • [2022] Subspace Clustering for Hyperspectral Images via Dictionary Learning With Adaptive Regularization, IEEE TGRS [Paper] [Python]
  • [2022] Superpixel Contracted Neighborhood Contrastive Subspace Clustering Network for Hyperspectral Images, IEEE TGRS [Paper]
  • [2022] Graph Regularized Spatial-spectral Subspace Clustering for Hyperspectral Band Selection, Neural Networks [Paper] [Matlab]
  • [2021] A Fast and Accurate Similarity-Constrained Subspace Clustering Algorithm for Hyperspectral Image, IEEE JSTARS [Paper] [Matlab]
  • [2021] Deep Spatial-Spectral Subspace Clustering for Hyperspectral Image, IEEE TCSVT [Paper]
  • [2021] Subspace Clustering for Hyperspectral Images via Dictionary Learning With Adaptive Regularization, IEEE TGRS [Paper]
  • [2021] Hybrid-Hypergraph Regularized Multiview Subspace Clustering for Hyperspectral Images, IEEE TGRS [Paper]
  • [2020] Multi-Objective Sparse Subspace Clustering for Hyperspectral Imagery, IEEE TGRS [Paper]
  • [2020] Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image, IEEE TGRS [Paper] [Python]
  • [2019] Laplacian-Regularized Low-Rank Subspace Clustering for Hyperspectral Image Band Selection, IEEE TGRS [Paper]

Denoising

  • [2024] Eigen-CNN: Eigenimages Plus Eigennoise Level Maps Guided Network for Hyperspectral Image Denoising, IEEE TGRS [Paper] [Matlab]
  • [2024] Full-Mode-Augmentation Tensor-Train Rank Minimization for Hyperspectral Image Inpainting, IEEE TGRS [Paper]
  • [2024] Hyperspectral Compressive Snapshot Reconstruction via Coupled Low-Rank Subspace Representation and Self-Supervised Deep Network, IEEE TIP [Paper] [Python]
  • [2024] Learnable Representative Coefficient Image Denoiser for Hyperspectral Image, IEEE TGRS [Paper] [Python]
  • [2023] Combining Low-Rank and Deep Plug-and-Play Priors for Snapshot Compressive Imaging , IEEE TNNLS [Paper]
  • [2023] FastHyMix: Fast and Parameter-Free Hyperspectral Image Mixed Noise Removal, IEEE TNNLS [Paper] [Matlab]
  • [2023] A New Nonconvex Low-Rank Tensor Approximation Method with Applications to Hyperspectral Images Denoising, Inverse Problems [Paper]
  • [2023] Tuning-free Plug-and-Play Hyperspectral Image Deconvolution with Deep Priors, IEEE TGRS [Paper] [Python]
  • [2023] Content-Aware Subspace Low-Rank Tensor Recovery for Hyperspectral Image Restoration, IEEE TGRS [Paper]
  • [2023] Deep Tensor Attention Prior Network for Hyperspectral Image Denoising, IEEE JSTARS [Paper]
  • [2023] Hyperspectral Image Denoising via Weighted Multidirectional Low-Rank Tensor Recovery, IEEE TC [Paper]
  • [2023] Nonlocal Structured Sparsity Regularization Modeling for Hyperspectral Image Denoising, IEEE TGRS [Paper]
  • [2023] Combined Deep Priors With Low-Rank Tensor Factorization for Hyperspectral Image Restoration, IEEE GRSL [Paper]
  • [2023] Multitask Sparse Representation Model-Inspired Network for Hyperspectral Image Denoising, IEEE TGRS [Paper]
  • [2022] Non-Local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration, IEEE TPAMI [Paper] [Matlab]
  • [2022] SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising, IEEE TIP [Paper] [Python]
  • [2022] Fast Noise Removal in Hyperspectral Images via Representative Coefficient Total Variation, IEEE TGRS [Paper] [Matlab]
  • [2022] Hyperspectral Image Denoising by Asymmetric Noise Modeling, IEEE TGRS [Paper]
  • [2022] Deep Plug-and-Play Prior for Hyperspectral Image Restoration, Neurocomputing [Paper] [Python]
  • [2022] Adaptive Rank and Structured Sparsity Corrections for Hyperspectral Image Restoration, IEEE TC [Paper]
  • [2022] Cooperated Spectral Low-Rankness Prior and Deep Spatial Prior for HSI Unsupervised Denoising, IEEE TIP [Paper]
  • [2022] Hyperspectral Image Denoising Using Spectral-Spatial Transform-Based Sparse and Low-Rank Representations, IEEE TGRS [Paper]
  • [2021] Multigraph-Based Low-Rank Tensor Approximation for Hyperspectral Image Restoration, IEEE TGRS [Paper] [Matlab]
  • [2021] Hy-Demosaicing: Hyperspectral Blind Reconstruction From Spectral Subsampling, IEEE TGRS [Paper] [Matlab]
  • [2021] LR-Net: Low-Rank Spatial-Spectral Network for Hyperspectral Image Denoising, IEEE TIP [Paper]
  • [2021] A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration, NIPS [Paper] [Python]
  • [2021] L0-L1 Hybrid Total Variation Regularization and its Applications on Hyperspectral Image Mixed Noise Removal and Compressed Sensing, IEEE TGRS [Paper] [Matlab]
  • [2021] MAC-Net: Model Aided Nonlocal Neural Network for Hyperspectral Image Denoising, IEEE TGRS [Paper] [Python]
  • [2021] Hyperspectral Image Restoration by Tensor Fibered Rank Constrained Optimization and Plug-and-Play Regularization, IEEE TGRS [Paper] [Matlab]
  • [2021] Total Variation Regularized Weighted Tensor Ring Decomposition for Missing Data Recovery in High-Dimensional Optical Remote Sensing Images, IEEE GRSL [Paper] [Matlab]
  • [2021] Hyperspectral Image Denoising via Low-Rank Representation and CNN Denoiser, IEEE JSTARS [Paper]
  • [2020] Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral Image, IEEE TGRS [Paper] [Matlab]
  • [2020] Hyperspectral Image Restoration via CNN Denoiser Prior Regularized Low-Rank Tensor Recovery, Computer Vision and Image Understanding [Paper] [Python]
  • [2019] Hyperspectral Image Denoising via Matrix Factorization and Deep Prior Regularization, IEEE TIP [Paper]
  • [2018] Hyperspectral Image Restoration Via Total Variation Regularized Low-Rank Tensor Decomposition, IEEE JSTARS [Paper] [Matlab]

Detection

  • [2024] Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection, arXiv [Paper][Python]
  • [2023] Anomaly Detection for Hyperspectral Imagery via Tensor Low-Rank Approximation With Multiple Subspace Learning, IEEE TGRS [Paper]
  • [2023] Learning Tensor Low-Rank Representation for Hyperspectral Anomaly Detection, IEEE TC [Paper] [Matlab]
  • [2023] A Model-Driven Deep Mixture Network for Robust Hyperspectral Anomaly Detection, IEEE TGRS [Paper]
  • [2023] LRR-Net: An Interpretable Deep Unfolding Network for Hyperspectral Anomaly Detection, IEEE TGRS [Paper]
  • [2023] Hyperspectral Anomaly Detection via Structured Sparsity Plus Enhanced Low-Rankness, IEEE TGRS [Paper]
  • [2022] Hyperspectral Anomaly Detection With Relaxed Collaborative Representation, IEEE TGRS [Paper]
  • [2022] Deep Low-Rank Prior for Hyperspectral Anomaly Detection, IEEE TGRS [Paper]
  • [2022] Prior-Based Tensor Approximation for Anomaly Detection in Hyperspectral Imagery, IEEE TNNLS [Paper][Matlab]
  • [2022] Hyperspectral Anomaly Detection With Tensor Average Rank and Piecewise Smoothness Constraints, IEEE TNNLS [Paper]
  • [2022] Tensor Recovery With Weighted Tensor Average Rank, IEEE TNNLS [Paper][Matlab]
  • [2022] Tensor Decomposition-Inspired Convolutional Autoencoders for Hyperspectral Anomaly Detection, IEEE JSTARS [Paper]
  • [2022] Moving Vehicle Detection for Remote Sensing Video Surveillance with Nonstationary Satellite Platform, IEEE TPAMI [Paper]
  • [2021] Hyperspectral Anomaly Detection via Deep Plug-and-Play Denoising CNN Regularization, IEEE TGRS [Paper][Matlab]
  • [2020] Graph and Total Variation Regularized Low-Rank Representation for Hyperspectral Anomaly Detection, IEEE TGRS [Paper]
  • [2020] Deep Plug-and-play Prior for Low-rank Tensor Completion, Neurocomputing [Paper] [Matlab]
  • [2016] Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation, IEEE TGRS [Paper] [Matlab]
  • [2016] A Tensor Decomposition-Based Anomaly Detection Algorithm for Hyperspectral Image, IEEE TGRS [Paper]
  • [2015] Background Subtraction Based on Low-Rank and Structured Sparse Decomposition, IEEE TIP [Paper] [Matlab]

Fusion

  • [2023] LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images, IEEE TPAMI [Paper] [Python]
  • [2023] Integrated Spatio-Spectral–Temporal Fusion via Anisotropic Sparsity Constrained Low-Rank Tensor Approximation, IEEE TGRS [Paper]
  • [2023] Distributed Nonlocal Coupled Hierarchical Tucker Decomposition for Hyperspectral Image Fusion, IEEE GRSL [Paper]
  • [2022] MHF-Net: An Interpretable Deep Network for Multispectral and Hyperspectral Image Fusion, IEEE TPAMI [Paper] [Python]
  • [2022] ADMM-HFNet: A Matrix Decomposition-Based Deep Approach for Hyperspectral Image Fusion, IEEE TGRS [Paper] [Python]
  • [2022] NMF-DuNet: Nonnegative Matrix Factorization Inspired Deep Unrolling Networks for Hyperspectral and Multispectral Image Fusion, IEEE JSTARS [Paper]
  • [2022] MLR-DBPFN: A Multi-Scale Low Rank Deep Back Projection Fusion Network for Anti-Noise Hyperspectral and Multispectral Image Fusion, IEEE TGRS [Paper]
  • [2021] Hyperspectral Restoration and Fusion with Multispectral Imagery by Recasting Low-Rank Tensor Approximation, IEEE TGRS [Paper] [Matlab]
  • [2021] Fusion of Hyperspectral and Multispectral Images Accounting for Localized Inter-Image Changes, IEEE TGRS [Paper] [Matlab]
  • [2021] Hyperspectral and Multispectral Image Fusion via Graph Laplacian-Guided Coupled Tensor Decomposition, IEEE TGRS [Paper]
  • [2021] Hyperspectral and Multispectral Image Fusion via Nonlocal Low-Rank Tensor Approximation and Sparse Representation, IEEE TGRS [Paper]
  • [2021] Hyperspectral-Multispectral Image Fusion via Tensor Ring and Subspace Decompositions, IEEE JSTARS [Paper]
  • [2021]Graph-Based Logarithmic Low-Rank Tensor Decomposition for the Fusion of Remotely Sensed Images, IEEE JSTARS [Paper]
  • [2021] Regularizing Hyperspectral and Multispectral Image Fusion by CNN Denoiser, IEEE TNNLS [Paper]
  • [2020] Nonlocal Coupled Tensor CP Decomposition for Hyperspectral and Multispectral Image Fusion, IEEE TGRS [Paper]
  • [2020] Image Fusion via Sparse Regularization with Non-Convex Penalties, Pattern Recognition Letters [Paper]
  • [2020] Hyperspectral and Multispectral Image Fusion via Nonlocal Low-Rank Tensor Decomposition and Spectral Unmixing, IEEE TGRS [Paper]
  • [2020] Nonlocal Sparse Tensor Factorization for Semiblind Hyperspectral and Multispectral Image Fusion, IEEE TC [Paper]
  • [2018] Spatial–Spectral-Graph-Regularized Low-Rank Tensor Decomposition for Multispectral and Hyperspectral Image Fusion, IEEE JSTARS [Paper]

Pansharpening

  • [2023] Pansharpening With Spatial Hessian Non-Convex Sparse and Spectral Gradient Low Rank Priors, IEEE TIP [Paper]
  • [2023] Pansharpening Method Based on Deep Nonlocal Unfolding, IEEE TGRS [Paper]
  • [2023] Unsupervised Pansharpening via Low-rank Diffusion Model，arXiv [Paper] [Python]
  • [2023] LRTCFPan: Low-Rank Tensor Completion Based Framework for Pansharpening, IEEE TIP [Paper] [Matlab]
  • [2023] PanFlowNet: A Flow-Based Deep Network for Pan-sharpening, ICCV [Paper] [Python]
  • [2022] Panchromatic and Hyperspectral Image Fusion: Outcome of the 2022 WHISPERS Hyperspectral Pansharpening Challenge, IEEE JSTARS [Paper] [Matlab]
  • [2022] A Unified Pansharpening Method With Structure Tensor Driven Spatial Consistency and Deep Plug-and-Play Priors, IEEE TGRS [Paper]
  • [2021] PanCSC-Net: A Model-Driven Deep Unfolding Method for Pansharpening, IEEE TGRS [Paper] [Python]
  • [2021] A Nonconvex Pansharpening Model With Spatial and Spectral Gradient Difference-Induced Nonconvex Sparsity Priors, IEEE TGRS [Paper]
  • [2021] Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction, IEEE TGRS [Paper] [Python]
  • [2020] Hyperspectral Pansharpening With Deep Priors, IEEE TGRS [Paper]
  • [2018] Learning Low-Rank Decomposition for Pan-Sharpening With Spatial-Spectral Offsets, IEEE TNNLS [Paper]
  • [2018] Pansharpening With Multiscale Geometric Support Tensor Machine, IEEE TGRS [Paper]
  • [2017] A Joint Sparse and Low-Rank Decomposition for Pansharpening of Multispectral Images, IEEE TGRS [Paper]
  • [2014] Pansharpening Based on Low-Rank and Sparse Decomposition, IEEE JSTARS [Paper]

Superresolution

  • [2024] Building Bridges across Spatial and TemporalResolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model, CVPR [Paper] [Python]
  • [2023] Bayesian Nonlocal Patch Tensor Factorization for Hyperspectral Image Super-Resolution, IEEE TIP [Paper]
  • [2022] Hyperspectral Image Super-Resolution via Deep Prior Regularization With Parameter Estimation, IEEE TCSVT [Paper] [Python]
  • [2022] Hyperspectral Super-Resolution via Coupled Tensor Ring Factorization, Pattern Recognition [Paper]
  • [2022] Hyperspectral Image Super-resolution with Deep Priors and Degradation Model Inversion, IEEE ICASSP [Paper] [Matlab]
  • [2022] An Iterative Regularization Method Based on Tensor Subspace Representation for Hyperspectral Image Super-Resolution, IEEE TGRS [Paper] [Matlab]
  • [2021] Model-Guided Deep Hyperspectral Image Super-Resolution, IEEE TIP [Paper] [Python]
  • [2021] Spatial-Spectral Structured Sparse Low-Rank Representation for Hyperspectral Image Super-Resolution, IEEE TIP [Paper]
  • [2021] Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning, IEEE TGRS [Paper] [Matlab]
  • [2020] Nonnegative and Nonlocal Sparse Tensor Factorization-Based Hyperspectral Image Super-Resolution, IEEE TGRS [Paper]
  • [2020] Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery, IEEE TCI [Paper]
  • [2020] Hyperspectral Images Super-Resolution via Learning High-Order Coupled Tensor Ring Representation, IEEE TNNLS [Paper]
  • [2020] Weighted Low-Rank Tensor Recovery for Hyperspectral Image Restoration, IEEE TC [Paper]
  • [2019] Nonlocal Patch Tensor Sparse Representation for Hyperspectral Image Super-Resolution, IEEE TIP [Paper]
  • [2019] Hyperspectral Image Super-Resolution via Subspace-Based Low Tensor Multi-Rank Regularization, IEEE TIP [Paper]
  • [2019] Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution, IEEE TNNLS [Paper]
  • [2016] Hyperspectral Image Super-Resolution via Non-Negative Structured Sparse Representation, IEEE TIP [Paper]
  • [2014] Sparse Spatio-spectral Representation for Hyperspectral Image Super Resolution, ECCV [Paper] [Matlab]

Unmixing

  • [2023] Unrolling Nonnegative Matrix Factorization With Group Sparsity for Blind Hyperspectral Unmixing, IEEE TGRS [Paper]
  • [2023] Hyperspectral Unmixing Using Higher-Order Graph Regularized NMF With Adaptive Feature Selection, IEEE TGRS [Paper]
  • [2023] Adaptive Hypergraph Regularized Multilayer Sparse Tensor Factorization for Hyperspectral Unmixing, IEEE TGRS [Paper]
  • [2022] UnDIP: Hyperspectral Unmixing Using Deep Image Prior, IEEE TGRS [Paper] [Python]
  • [2022] Hyperspectral Sparse Unmixing via Nonconvex Shrinkage Penalties, IEEE TGRS [Paper]
  • [2022] Efficient Weighted-Adaptive Sparse Constrained Nonnegative Tensor Factorization for Hyperspectral Unmixing, IEEE TGRS [Paper]
  • [2022] SNMF-Net: Learning a Deep Alternating Neural Network for Hyperspectral Unmixing, IEEE TGRS [Paper] [Python]
  • [2022] A Plug-and-Play Priors Framework for Hyperspectral Unmixing, IEEE TGRS [Paper] [Matlab]
  • [2021] Nonlocal Tensor-Based Sparse Hyperspectral Unmixing, IEEE TGRS [Paper]
  • [2021] Hyperspectral Unmixing via Nonnegative Matrix Factorization With Handcrafted and Learned Priors, IEEE GRSL [Paper]
  • [2021] Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing, IEEE JSTARS [Paper]
  • [2021] Hyperspectral Unmixing Using Nonlocal Similarity-Regularized Low-Rank Tensor Factorization, IEEE TGRS [Paper]
  • [2021] Sparsity-Enhanced Convolutional Decomposition: A Novel Tensor-Based Paradigm for Blind Hyperspectral Unmixing, IEEE TGRS [Paper][Matlab]
  • [2021] Using Low-Rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing, IEEE TGRS [Paper][Matlab]
  • [2021] Clustering by Orthogonal NMF Model and Non-Convex Penalty Optimization, IEEE TIP [Paper] [Matlab]
  • [2020] Sparsity-Constrained Coupled Nonnegative Matrix–Tensor Factorization for Hyperspectral Unmixing, IEEE JSTARS [Paper]
  • [2020] Weighted Nonlocal Low-Rank Tensor Decomposition Method for Sparse Unmixing of Hyperspectral Images, IEEE JSTARS [Paper]
  • [2019] Hyperspectral Unmixing via Total Variation Regularized Nonnegative Tensor Factorization, IEEE TGRS [Paper] [Matlab]
  • [2018] Hyperspectral Unmixing Using Sparsity-Constrained Deep Nonnegative Matrix Factorization with Total Variation, IEEE TGRS [Paper]
  • [2017] Spatial Group Sparsity Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing, IEEE TGRS [Paper][Matlab]
  • [2017] SRCMF: Robust Constrained Matrix Factorization for Hyperspectral Unmixing, IEEE TGRS [Paper] [Matlab]

Links

Journals

  • Remote Sensing of Environment [Link]
  • ISPRS Journal of Photogrammetry and Remote Sensing [Link]
  • IEEE Transactions on Geoscience and Remote Sensing [Link]

Tools

  • Satellite Image Deep Learning [Link]
  • Hyperspectral Anomaly Detection Algorithms [Link]
  • Hyperspectral Imag Denoising Benchmark [Link]